Watson, Come Here, We Need You

A machine named Watson became the new Jeopardy champion on national television last night. Another supposedly uniquely human achievement, mastery of trivia game shows, fell, just like chess did a few years ago. What should we make of it?

For some, the event echoes the apocalyptic science fiction of the 1950's, where computers, or robots, or space aliens intervene to "take over" from humanity. Sometimes it's benevolent, "for our own good" to "save us from ourselves" as in The Day the Earth Stood Still or any number of Isaac Asimov stories featuring omniscient supercomputers or mind-reading robots. Sometimes it is the "end of humanity" at least as we've known it, as in Colossus: The Forbin Project.

I take a different view, based on evolutionary biology. Since my formal education and business experience is in computer science, I tend to look at evolution in terms of information. For the first few billion years of life on Earth, single cell organisms were limited to the information stored in the DNA in their nucleus. That information dictated the entire behavior and capability of that species of micro-critter.

Then life developed multi-cellular organisms, starting with plaques and mats of identical bacteria, but then plants and animals. Animals developed nerves and brains. With brains, animals developed a way of storing information outside the cell nucleus, coded in proteins. With nerves, animals developed ways to collect and act on information.

Animals can learn from experience, and from each other. Anyone who watches nature shows sees the process of a baby elephant learning to be an elephant, or a baby wolf learning to be a wolf. And it makes us humans feel warm and fuzzy inside, because we do the same thing: teach baby humans to be humans.

But there is one thing we teach our young that no other species does - not even very intelligent species like chimpanzees or whales. We teach our young how to read and write. You see, we are the only species on our planet that has learned how to store information outside our physical bodies.

At first, the information we could store was clumsy and limited: scratches on rocks or marks on tree bark. It was not the amount of information we stored outside our bodies that mattered, but its persistence through space and time. By writing and reading, people can learn from other people who they have never met and never will meet. We can literally learn from the dead, as well as the distant, because we can read what they wrote.

No other animal on Earth can do that. It makes what we call civilization possible. And with civilization, we gained mastery of other plants, animals, and the environment, increasingly able to make them serve our needs and wants.

Our ways of storing information improved with time. We invented paper, ink, and the printing press. We tamed lightning, and found that electricity, magnetism, and light could be harnessed to move, store, and process information far faster and in far greater volume.

We get better and better at learning. Over 90% of what humanity knows, about everything, was learned during my lifetime. About every 2 years, the total amount of information we have doubles. How can we possibly keep up?

The earliest good answer came not from science fiction, but from romantic comedy. In the 1957 classic, Desk Set, the research department at the fictional Federal Broadcasting Network is set a-twitter by a new-fangled computer called EMERAC and the aging boy genius behind it, played by Spencer Tracy. Scriptwriters Phoebe and Henry Ephron and the original playwright William Marchant envisioned EMERAC as, well, Google in a box - a very big, temperamental box. In other words, a search engine.

Of course, everyone is afraid that the computer will replace them, and all of the plot complications revolve around that notion. But at the end of the movie, we learn that the research department is about to be swamped with more work, and even with EMERAC, they need to hire more good people to keep up.

In one of her best roles, Katherine Hepburn played the head of the research department and Spencer Tracy's love interest. Because she knows what is the right question and when the answer coming back is simply nonsense, she ends up with the job, the guy, and the credit. The president of the network wants more people like her, people who can get the best out of both man and machine.